/// <summary>
/// Generates output predictions for the input samples. Computation is done in batches.
/// </summary>
/// <param name="x">The input data frame to run prediction.</param>
/// <param name="batch_size">Size of the batch.</param>
/// <returns></returns>
public DataFrame Predict(DataFrame x, int batch_size)
{
DataFrameIter dataFrameIter = new DataFrameIter(x);
List <float> predictions = new List <float>();
dataFrameIter.SetBatchSize(batch_size);
while (dataFrameIter.Next())
{
var data = dataFrameIter.GetBatchX();
Tensor output = data;
foreach (var layer in Layers)
{
if (layer.SkipPred)
{
continue;
}
layer.Forward(output);
output = layer.Output;
}
predictions.AddRange(output.ToArray().Cast <float>());
}
DataFrame result = new DataFrame();
result.Load(predictions.ToArray());
return(result);
}
/// <summary>
/// Generates output predictions for the input samples.
/// </summary>
/// <param name="x">The input data frame to run prediction.</param>
/// <returns></returns>
public DataFrame Predict(DataFrame x)
{
List <float> predictions = new List <float>();
Tensor output = x.GetTensor();
foreach (var layer in Layers)
{
if (layer.SkipPred)
{
continue;
}
layer.Forward(output);
output = layer.Output;
}
predictions.AddRange(output.ToArray().Cast <float>());
DataFrame result = new DataFrame();
result.Load(predictions.ToArray());
return(result);
}